Data science courses

Master marketing analytics using Tableau. Analyze performance, benchmark metrics, and optimize strategies across channels.

Develop the skills you need to clean raw data and transform it into accurate insights.

Learn how to use Python to analyze customer churn and build a model to predict it.

Learn to streamline your machine learning workflows with tidymodels.

Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.

Discover how to analyze and visualize baseball data using Power BI. Create scatter plots, tornado charts, and gauges to bring baseball insights alive.

In ecommerce, increasing sales and reducing costs are key. Analyze data from an online pet supply company using Power BI.

Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.

From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.

Learn how to load, transform, and transcribe speech from raw audio files in Python.

Prepare for your next statistics interview by reviewing concepts like conditional probabilities, A/B testing, the bias-variance tradeoff, and more.

Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.

Learn how to design and implement triggers in SQL Server using real-world examples.

Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.

Learn how to use plotly in R to create interactive data visualizations to enhance your data storytelling.

In this course, you’ll learn to classify, treat and analyze time series; an absolute must, if you’re serious about stepping up as an analytics professional.

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.

Learn how to visualize time series in R, then practice with a stock-picking case study.

In this course youll learn how to perform inference using linear models.

Learn to use R to develop models to evaluate and analyze bonds as well as protect them from interest rate changes.

Learn how to pull character strings apart, put them back together and use the stringr package.

Learn how to build a model to automatically classify items in a school budget.

Learn efficient techniques in pandas to optimize your Python code.

Learn to use the Census API to work with demographic and socioeconomic data.

Learn to process sensitive information with privacy-preserving techniques.

Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.

Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.

Gain the essential skills using Scikit-learn, SHAP, and LIME to test and build transparent, trustworthy, and accountable AI systems.